Google Exam Professional-Data-Engineer Topic 6 Question 77 Discussion

Actual exam question for Google's Google Cloud Certified Professional Data Engineer exam

Question #: 77
Topic #: 6

[All Google Cloud Certified Professional Data Engineer Questions]

You need to look at BigQuery data from a specific table multiple times a day. The underlying table you are querying is several petabytes in size, but you want to filter your data and provide simple aggregations to downstream users. You want to run queries faster and get up-to-date insights quicker. What should you do?

ARun a scheduled query to pull the necessary data at specific intervals daily.

BCreate a materialized view based off of the query being run.

CUse a cached query to accelerate time to results.

DLimit the query columns being pulled in the final result.

Show Suggested Answer

Suggested Answer: B

Materialized views are precomputed views that periodically cache the results of a query for increased performance and efficiency. BigQuery leverages precomputed results from materialized views and whenever possible reads only changes from the base tables to compute up-to-date results. Materialized views can significantly improve the performance of workloads that have the characteristic of common and repeated queries. Materialized views can also optimize queries with high computation cost and small dataset results, such as filtering and aggregating large tables. Materialized views are refreshed automatically when the base tables change, so they always return fresh data. Materialized views can also be used by the BigQuery optimizer to process queries to the base tables, if any part of the query can be resolved by querying the materialized view.Reference:

Introduction to materialized views

Create materialized views

BigQuery Materialized View Simplified: Steps to Create and 3 Best Practices

Materialized view in Bigquery

by Jani at Feb 07, 2024, 06:56 AM

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6 months ago

I agree, a materialized view seems like the way to go. With a table that size, we need to be proactive about optimizing our queries. And B gives us the added benefit of keeping the data fresh without having to run a full query every time.

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6 months ago

Hmm, this is a tricky one. The table is massive, so we need to be smart about how we access the data. A scheduled query could work, but it might not give us the most up-to-date insights. I'm leaning towards option B - creating a materialized view. That way, we can preload the data we need and get faster results.

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